A robust simulated annealing based examination timetabling system
Computers and Operations Research
An Experimental Evaluation of a Scatter Search for the Linear Ordering Problem
Journal of Global Optimization
A Survey of Automated Timetabling
Artificial Intelligence Review
The Complexity of Timetable Construction Problems
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
Examination Timetabling in British Universities: A Survey
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
A Language for Specifying Complete Timetabling Problems
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
Tabu Search Techniques for Examination Timetabling
PATAT '00 Selected papers from the Third International Conference on Practice and Theory of Automated Timetabling III
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Scatter Search: Methodology and Implementations in C
Scatter Search: Methodology and Implementations in C
A multi-objective evolutionary algorithm for examination timetabling
Journal of Scheduling
INFORMS Journal on Computing
A perspective on bridging the gap between theory and practice in university timetabling
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
Linear linkage encoding in grouping problems: applications on graph coloring and timetabling
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
An experimental study on hyper-heuristics and exam timetabling
PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
A hybrid multi-objective evolutionary algorithm for the uncapacitated exam proximity problem
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Fuzzy multiple heuristic orderings for examination timetabling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
A multistage evolutionary algorithm for the timetable problem
IEEE Transactions on Evolutionary Computation
A graph coloring constructive hyper-heuristic for examination timetabling problems
Applied Intelligence
Managing dynamic CSPs with preferences
Applied Intelligence
Parallel Scatter Search Algorithms for Exam Timetabling
International Journal of Applied Metaheuristic Computing
A hierarchical parallel genetic approach for the graph coloring problem
Applied Intelligence
On the performance of Scatter Search for post-enrolment course timetabling problems
Journal of Combinatorial Optimization
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At universities where students enjoy flexibility in selecting courses, the Registrar's office aims to generate an appropriate exam timetable for numerous courses and large number of students. An appropriate, real-world exam timetable should show fairness towards all students, respecting the following constraints: (a) eliminating or minimizing the number of simultaneous exams; (b) minimizing the number of consecutive exams; (c) minimizing the number of students with two or three exams per day (d) eliminating the possibility of more than three exams per day (e) exams should fit in rooms with predefined capacity; and (f) the number of exam periods is limited. These constraints are conflicting, which makes exam timetabling intractable. Hence, solving this problem in realistic time requires the use of heuristic approaches. In this work, we develop an evolutionary heuristic technique based on the scatter search approach for finding good suboptimal solutions for exam timetabling. This approach is based on maintaining and evolving a population of solutions. We evaluate our suggested technique on real-world university data and compare our results with the registrar's manual timetable in addition to the timetables of other heuristic optimization algorithms. The experimental results show that our adapted scatter search technique generates better timetables than those produced by the registrar, manually, and by other meta-heuristics.